A new gravity model with variable distance decay

Our main goal is to understand the customers' store choice behavior in a grocery retail setting. We see this as a first vital step in order to make store location, format and product promotion decisions in the retail organization Proposed models in the literature generate consumer utility functions for different stores which are used in store sales estimation. For example, in one of its basic forms, Huff model proposes that, utility of a store for an individual is equal to the sales area of the store divided by a power of the individual's distance to the store. Parallel to this stream of research Multiplicative Competitor Interaction model estimates log-transformed utility functions by ordinary least squares regression. It is less specific in terms of variable selection compared to the Huff model. This paper proposes a new market share model which is a variant of the Huff model and evaluates most established market share models such as Huff and Multiplicative Competitor Interaction Model as well as a data mining method in a one-brand heterogonous size retail store setting. We observe that the Huff model performs well in its basic form. By representing distance decay value as a function of the sales area of the retail store we are able to improve the performance of the Huff model. We propose using optimization for estimating the model parameters in certain cases and observe that this improves the generalization ability of the model.